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Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
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Flood mitigation data analytics and decision support framework: Iowa Middle Cedar Watershed case study.

Yazeed Alabbad1, Enes Yildirim2, Ibrahim Demir3

  • 1Department of Civil and Environmental Engineering, University of Iowa, Iowa City, IA, USA; Department of Civil Engineering, King Saud University, Riyadh, Saudi Arabia.

The Science of the Total Environment
|January 6, 2022
PubMed
Summary
This summary is machine-generated.

Flood mitigation strategies can significantly reduce property damage and vulnerability. A new system, MiDAS, helps communities analyze risks and choose cost-effective flood protection measures for better disaster preparedness.

Keywords:
Data analyticsDecision supportFlood mitigationFlood riskFloodproofing

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Area of Science:

  • Environmental science and disaster management.
  • Civil engineering and urban planning.
  • Risk assessment and decision support systems.

Background:

  • Flooding is a frequent natural disaster causing substantial economic damage and threatening communities globally.
  • Effective flood mitigation requires comprehensive analysis of risks, damages, and cost-benefit comparisons of various strategies.
  • Existing decision-making processes for flood mitigation can be complex and require informed guidance.

Purpose of the Study:

  • To introduce a web-based decision support framework, the Mitigation and Damage Assessment System (MiDAS).
  • To analyze flood risk impacts and evaluate mitigation strategies at community and property levels.
  • To inform communities about flood consequences and encourage participation in rating systems.

Main Methods:

  • Utilizing regulatory flood inundation maps, damage functions, property data, and climate projections.
  • Incorporating mitigation guidelines from the Federal Emergency Management Agency (FEMA) and the United States Army Corps of Engineers (USACE).
  • Developing a decision tree algorithm for analyzing and representing mitigation choices based on property characteristics and cost-benefit analysis.

Main Results:

  • Identified cost-effective community-level mitigation measures, such as wet/dry floodproofing, in three Eastern Iowa cities.
  • Demonstrated that implementing mitigation measures can reduce property vulnerability and enhance flood response.
  • The MiDAS framework provides cost estimates and aids in selecting appropriate flood mitigation strategies.

Conclusions:

  • The MiDAS system offers a valuable tool for communities to make informed decisions regarding flood risk and mitigation.
  • Strategic implementation of flood mitigation measures is crucial for long-term protection and resilience.
  • Encouraging community participation in rating systems can be facilitated by accessible decision support tools like MiDAS.